Incorporating Uncertainty in Learning to Defer Algorithms for Safe Computer-Aided Diagnosis

In this study we propose the Learning to Defer with Uncertainty (LDU) algorithm, an approach which considers the model's predictive uncertainty when identifying the patient group to be evaluated by human experts. Our aim is to ensure patient safety when ML models are deployed in healthcare settings.